Cowpea mosaic virus (CPMV) is a plant comovirus in the picornavirus superfamily, and is used for a wide variety of biomedical and material science applications. Although its replication is restricted to plants, CPMV binds to and enters mammalian cells, including endothelial cells and particularly tumor neovascular endothelium in vivo. This natural capacity has lead to the use of CPMV as a sensor for intravital imaging of vascular development. Binding of CPMV to endothelial cells occurs via interaction with a 54 kD cell-surface protein, but this protein has not previously been identified. Here we identify the CPMV binding protein as a cell-surface form of the intermediate filament vimentin. The CPMV-vimentin interaction was established using proteomic screens and confirmed by direct interaction of CPMV with purified vimentin, as well as inhibition in a vimentin-knockout cell line. Vimentin and CPMV were also co-localized in vascular endothelium of mouse and rat in vivo. Together these studies indicate that surface vimentin mediates binding and may lead to internalization of CPMV in vivo, establishing surface vimentin as an important vascular endothelial ligand for nanoparticle targeting to tumors. These results also establish vimentin as a ligand for picornaviruses in both the plant and animal kingdoms of life. Since bacterial pathogens and several other classes of viruses also bind to surface vimentin, these studies suggest a common role for surface vimentin in pathogen transmission.

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Mass spectrometry has become an indispensable tool for the global study of metabolites (metabolomics), primarily using electrospray ionization mass spectrometry (ESI-MS). However, many important classes of molecules such as neutral lipids do not ionize well by ESI and go undetected. Chemical derivatization of metabolites can enhance ionization for increased sensitivity and metabolomic coverage. Here we describe the use of tris(2,4,6,-trimethoxyphenyl)phosphonium acetic acid (TMPP-AA) to improve liquid chromatography (LC)/ESI-MS detection of hydroxylated metabolites (i.e. lipids) from serum extracts. Cholesterol which is not normally detected from serum using ESI is observed with attomole sensitivity. This approach was applied to identify four endogenous lipids (hexadecanoyl-sn-glycerol, dihydrotachysterol, octadecanol, and alpha-tocopherol) from human serum. Overall, this approach extends the types of metabolites which can be detected using standard ESI-MS instrumentation and demonstrates the potential for targeted metabolomics analysis.

Lymphocytic choriomeningitis virus (LCMV) infection of mice is noncytopathic, producing well-characterized changes reflecting the host immune response. Untargeted metabolomics using mass spectrometry identified endogenous small molecule changes in blood from mice inoculated with LCMV, sampled at days 1, 3, 7, and 14 post infection. These time points correspond to well characterized events during acute LCMV infection and the immune response. Diverse pathways were altered, including TCA cycle intermediates, gamma-glutamyl dipeptides, lysophosphatidyl cholines, and fatty acids. The kynurenine pathway was activated, surprising because it is stimulated by IFN-gamma, which LCMV suppresses, thus, suggesting alternative activators. In contrast, biopterin/neopterin, another IFN-gamma stimulated pathway, was not activated. Many metabolites followed "response and recovery" kinetics, decreasing after infection to a minimum at days 3-7, and returning to normal by day 14. The TCA pathway followed this pattern, including citrate, cis-aconitate and alpha-ketoglutarate, intriguing because succinate has been shown to mediate cellular immunity. This response and recovery dynamic tracks the immune response, including the rise and fall of natural killer cell populations, serum TNF receptor concentration, and viral clearance. Metabolomics can provide target pathways for molecular diagnostics or therapeutics of viral infection and immunity.

We have performed a comprehensive characterization of global molecular changes for a model organism Pyrococcus furiosus using transcriptomic (DNA microarray), proteomic, and metabolomic analysis as it undergoes a cold adaptation response from its optimal 95 to 72 degrees C. Metabolic profiling on the same set of samples shows the down-regulation of many metabolites. However, some metabolites are found to be strongly up-regulated. An approach using accurate mass, isotopic pattern, database searching, and retention time is used to putatively identify several metabolites of interest. Many of the up-regulated metabolites are part of an alternative polyamine biosynthesis pathway previously established in a thermophilic bacterium Thermus thermophilus. Arginine, agmatine, spermidine, and branched polyamines N4-aminopropylspermidine and N4-( N-acetylaminopropyl)spermidine were unambiguously identified based on their accurate mass, isotopic pattern, and matching of MS/MS data acquired under identical conditions for the natural metabolite and a high purity standard. Both DNA microarray and semiquantitative proteomic analysis using a label-free spectral counting approach indicate the down-regulation of a large majority of genes with diverse predicted functions related to growth such as transcription, amino acid biosynthesis, and translation. Some genes are, however, found to be up-regulated through the measurement of their relative mRNA and protein levels. The complimentary information obtained by the various "omics" techniques is used to catalogue and correlate the overall molecular changes.

The Escherichia coli small (30S) ribosomal subunit is a particularly well-characterized model system for studying in vitro self-assembly. A previously developed pulse-chase monitored by quantitative mass spectrometry (PC/QMS) approach to measuring kinetics of in vitro 30S assembly suffered from poor signal-to-noise and was unable to observe some ribosomal proteins. We have developed an improved LC-MS based method using quantitative ESI-TOF analysis of isotope-labeled tryptic peptides. Binding rates for 18 of the 20 ribosomal proteins are reported, and exchange of proteins S2 and S21 between bound and unbound states prevented measurement of their binding kinetics. Multiphasic kinetics of 3' domain proteins S7 and S9 are reported, which support an assembly mechanism that utilizes multiple parallel pathways. This quantitative ESI-TOF approach should be widely applicable to study the assembly of other macromolecular complexes and to quantitative proteomics experiments in general.

Mass spectrometry based metabolomics represents a new area for bioinformatics technology development. While the computational tools currently available such as XCMS statistically assess and rank LC-MS features, they do not provide information about their structural identity. XCMS(2) is an open source software package which has been developed to automatically search tandem mass spectrometry (MS/MS) data against high quality experimental MS/MS data from known metabolites contained in a reference library (METLIN). Scoring of hits is based on a "shared peak count" method that identifies masses of fragment ions shared between the analytical and reference MS/MS spectra. Another functional component of XCMS(2) is the capability of providing structural information for unknown metabolites, which are not in the METLIN database. This "similarity search" algorithm has been developed to detect possible structural motifs in the unknown metabolite which may produce characteristic fragment ions and neutral losses to related reference compounds contained in METLIN, even if the precursor masses are not the same.

We have performed a comprehensive characterization of global molecular changes for a model organism Pyrococcus furiosus using transcriptomic (DNA microarray), proteomic, and metabolomic analysis as it undergoes a cold adaptation response from its optimal 95 to 72 degrees C. Metabolic profiling on the same set of samples shows the down-regulation of many metabolites. However, some metabolites are found to be strongly up-regulated. An approach using accurate mass, isotopic pattern, database searching, and retention time is used to putatively identify several metabolites of interest. Many of the up-regulated metabolites are part of an alternative polyamine biosynthesis pathway previously established in a thermophilic bacterium Thermus thermophilus. Arginine, agmatine, spermidine, and branched polyamines N4-aminopropylspermidine and N4-( N-acetylaminopropyl)spermidine were unambiguously identified based on their accurate mass, isotopic pattern, and matching of MS/MS data acquired under identical conditions for the natural metabolite and a high purity standard. Both DNA microarray and semiquantitative proteomic analysis using a label-free spectral counting approach indicate the down-regulation of a large majority of genes with diverse predicted functions related to growth such as transcription, amino acid biosynthesis, and translation. Some genes are, however, found to be up-regulated through the measurement of their relative mRNA and protein levels. The complimentary information obtained by the various "omics" techniques is used to catalogue and correlate the overall molecular changes.

The Escherichia coli small (30S) ribosomal subunit is a particularly well-characterized model system for studying in vitro self-assembly. A previously developed pulse-chase monitored by quantitative mass spectrometry (PC/QMS) approach to measuring kinetics of in vitro 30S assembly suffered from poor signal-to-noise and was unable to observe some ribosomal proteins. We have developed an improved LC-MS based method using quantitative ESI-TOF analysis of isotope-labeled tryptic peptides. Binding rates for 18 of the 20 ribosomal proteins are reported, and exchange of proteins S2 and S21 between bound and unbound states prevented measurement of their binding kinetics. Multiphasic kinetics of 3' domain proteins S7 and S9 are reported, which support an assembly mechanism that utilizes multiple parallel pathways. This quantitative ESI-TOF approach should be widely applicable to study the assembly of other macromolecular complexes and to quantitative proteomics experiments in general.

Mass spectrometry based metabolomics represents a new area for bioinformatics technology development. While the computational tools currently available such as XCMS statistically assess and rank LC-MS features, they do not provide information about their structural identity. XCMS(2) is an open source software package which has been developed to automatically search tandem mass spectrometry (MS/MS) data against high quality experimental MS/MS data from known metabolites contained in a reference library (METLIN). Scoring of hits is based on a "shared peak count" method that identifies masses of fragment ions shared between the analytical and reference MS/MS spectra. Another functional component of XCMS(2) is the capability of providing structural information for unknown metabolites, which are not in the METLIN database. This "similarity search" algorithm has been developed to detect possible structural motifs in the unknown metabolite which may produce characteristic fragment ions and neutral losses to related reference compounds contained in METLIN, even if the precursor masses are not the same.

Antibody affinity is critically important in therapeutic applications, as well as steady state diagnostic assays. Picomolar affinity antibodies, approaching the association limit of protein-protein interactions, have been discovered for highly potent antigens, but even such high-affinity binders have off-rates sufficient to negate therapeutic efficacy. To cross this affinity threshold, antibodies that tether their targets in a manner other than reversible non-covalent interaction will be required. Here we report the design and construction of an antibody that forms an irreversible complex with a protein antigen in a metal-dependent reaction. The complex resists thermal and chemical denaturation, as well as attempts to remove the coordinating metal ion. Such irreversibly binding antibodies could facilitate the development of next generation "reactive antibody" therapeutics and diagnostics.

A new and general methodology is described for the targeted enrichment and subsequent direct mass spectrometric characterization of sample subsets bearing various chemical functionalities from highly complex mixtures of biological origin. Specifically, sample components containing a chemical moiety of interest are first selectively labeled with perfluoroalkyl groups, and the entire sample is then applied to a perfluoroalkyl-silylated porous silicon (pSi) surface. Due to the unique hydrophobic and lipophobic nature of the perfluorinated tags, unlabeled sample components are readily removed using simple surface washes, and the enriched sample fraction can then directly be analyzed by desorption/ionization on silicon mass spectrometry (DIOS-MS). Importantly, this fluorous-based enrichment methodology provides a single platform that is equally applicable to both peptide as well as small molecule focused applications. The utility of this technique is demonstrated by the enrichment and mass spectrometric analysis of both various peptide subsets from protein digests as well as amino acids from serum.

Antibody affinity is critically important in therapeutic applications, as well as steady state diagnostic assays. Picomolar affinity antibodies, approaching the association limit of protein-protein interactions, have been discovered for highly potent antigens, but even such high-affinity binders have off-rates sufficient to negate therapeutic efficacy. To cross this affinity threshold, antibodies that tether their targets in a manner other than reversible non-covalent interaction will be required. Here we report the design and construction of an antibody that forms an irreversible complex with a protein antigen in a metal-dependent reaction. The complex resists thermal and chemical denaturation, as well as attempts to remove the coordinating metal ion. Such irreversibly binding antibodies could facilitate the development of next generation "reactive antibody" therapeutics and diagnostics.

A new and general methodology is described for the targeted enrichment and subsequent direct mass spectrometric characterization of sample subsets bearing various chemical functionalities from highly complex mixtures of biological origin. Specifically, sample components containing a chemical moiety of interest are first selectively labeled with perfluoroalkyl groups, and the entire sample is then applied to a perfluoroalkyl-silylated porous silicon (pSi) surface. Due to the unique hydrophobic and lipophobic nature of the perfluorinated tags, unlabeled sample components are readily removed using simple surface washes, and the enriched sample fraction can then directly be analyzed by desorption/ionization on silicon mass spectrometry (DIOS-MS). Importantly, this fluorous-based enrichment methodology provides a single platform that is equally applicable to both peptide as well as small molecule focused applications. The utility of this technique is demonstrated by the enrichment and mass spectrometric analysis of both various peptide subsets from protein digests as well as amino acids from serum.

The aim of metabolite profiling is to monitor all metabolites within a biological sample for applications in basic biochemical research as well as pharmacokinetic studies and biomarker discovery. Here, novel data analysis software, XCMS, was used to monitor all metabolite features detected from an array of serum extraction methods, with application to metabolite profiling using electrospray liquid chromatography/mass spectrometry (ESI-LC/MS). The XCMS software enabled the comparison of methods with regard to reproducibility, the number and type of metabolite features detected, and the similarity of these features between different extraction methods. Extraction efficiency with regard to metabolite feature hydrophobicity was examined through the generation of unique feature density distribution plots, displaying feature distribution along chromatographic time. Hierarchical clustering was performed to highlight similarities in the metabolite features observed between the extraction methods. Protein extraction efficiency was determined using the Bradford assay, and the residual proteins were identified using nano-LC/MS/MS. Additionally, the identification of four of the most intensely ionized serum metabolites using FTMS and tandem mass spectrometry was reported. The extraction methods, ranging from organic solvents and acids to heat denaturation, varied widely in both protein removal efficiency and the number of mass spectral features detected. Methanol protein precipitation followed by centrifugation was found to be the most effective, straightforward, and reproducible approach, resulting in serum extracts containing over 2000 detected metabolite features and less than 2% residual protein. Interestingly, the combination of all approaches produced over 10,000 unique metabolite features, a number that is indicative of the complexity of the human metabolome and the potential of metabolomics in biomarker discovery.

Mass spectrometry analysis was used to target three different aspects of the viral infection process: the expression kinetics of viral proteins, changes in the expression levels of cellular proteins, and the changes in cellular metabolites in response to viral infection. The combination of these methods represents a new, more comprehensive approach to the study of viral infection revealing the complexity of these events within the infected cell. The proteins associated with measles virus (MV) infection of human HeLa cells were measured using a label-free approach. On the other hand, the regulation of cellular and Flock House Virus (FHV) proteins in response to FHV infection of Drosophila cells was monitored using stable isotope labeling. Three complementary techniques were used to monitor changes in viral protein expression in the cell and host protein expression. A total of 1500 host proteins was identified and quantified, of which over 200 proteins were either up- or down-regulated in response to viral infection, such as the up-regulation of the Drosophila apoptotic croquemort protein, and the down-regulation of proteins that inhibited cell death. These analyses also demonstrated the up-regulation of viral proteins functioning in replication, inhibition of RNA interference, viral assembly, and RNA encapsidation. Over 1000 unique metabolites were also observed with significant changes in over 30, such as the down-regulated cellular phospholipids possibly reflecting the initial events in cell death and viral release. Overall, the cellular transformation that occurs upon viral infection is a process involving hundreds of proteins and metabolites, many of which are structurally and functionally uncharacterized.

The aim of metabolite profiling is to monitor all metabolites within a biological sample for applications in basic biochemical research as well as pharmacokinetic studies and biomarker discovery. Here, novel data analysis software, XCMS, was used to monitor all metabolite features detected from an array of serum extraction methods, with application to metabolite profiling using electrospray liquid chromatography/mass spectrometry (ESI-LC/MS). The XCMS software enabled the comparison of methods with regard to reproducibility, the number and type of metabolite features detected, and the similarity of these features between different extraction methods. Extraction efficiency with regard to metabolite feature hydrophobicity was examined through the generation of unique feature density distribution plots, displaying feature distribution along chromatographic time. Hierarchical clustering was performed to highlight similarities in the metabolite features observed between the extraction methods. Protein extraction efficiency was determined using the Bradford assay, and the residual proteins were identified using nano-LC/MS/MS. Additionally, the identification of four of the most intensely ionized serum metabolites using FTMS and tandem mass spectrometry was reported. The extraction methods, ranging from organic solvents and acids to heat denaturation, varied widely in both protein removal efficiency and the number of mass spectral features detected. Methanol protein precipitation followed by centrifugation was found to be the most effective, straightforward, and reproducible approach, resulting in serum extracts containing over 2000 detected metabolite features and less than 2% residual protein. Interestingly, the combination of all approaches produced over 10,000 unique metabolite features, a number that is indicative of the complexity of the human metabolome and the potential of metabolomics in biomarker discovery.

Mass spectrometry analysis was used to target three different aspects of the viral infection process: the expression kinetics of viral proteins, changes in the expression levels of cellular proteins, and the changes in cellular metabolites in response to viral infection. The combination of these methods represents a new, more comprehensive approach to the study of viral infection revealing the complexity of these events within the infected cell. The proteins associated with measles virus (MV) infection of human HeLa cells were measured using a label-free approach. On the other hand, the regulation of cellular and Flock House Virus (FHV) proteins in response to FHV infection of Drosophila cells was monitored using stable isotope labeling. Three complementary techniques were used to monitor changes in viral protein expression in the cell and host protein expression. A total of 1500 host proteins was identified and quantified, of which over 200 proteins were either up- or down-regulated in response to viral infection, such as the up-regulation of the Drosophila apoptotic croquemort protein, and the down-regulation of proteins that inhibited cell death. These analyses also demonstrated the up-regulation of viral proteins functioning in replication, inhibition of RNA interference, viral assembly, and RNA encapsidation. Over 1000 unique metabolites were also observed with significant changes in over 30, such as the down-regulated cellular phospholipids possibly reflecting the initial events in cell death and viral release. Overall, the cellular transformation that occurs upon viral infection is a process involving hundreds of proteins and metabolites, many of which are structurally and functionally uncharacterized.

Endogenous metabolites have gained increasing interest over the past 5 years largely for their implications in diagnostic and pharmaceutical biomarker discovery. METLIN (http://metlin.scripps.edu), a freely accessible web-based data repository, has been developed to assist in a broad array of metabolite research and to facilitate metabolite identification through mass analysis. METLINincludes an annotated list of known metabolite structural information that is easily cross-correlated with its catalogue of high-resolution Fourier transform mass spectrometry (FTMS) spectra, tandem mass spectrometry (MS/MS) spectra, and LC/MS data.

Endogenous metabolites have gained increasing interest over the past 5 years largely for their implications in diagnostic and pharmaceutical biomarker discovery. METLIN (http://metlin.scripps.edu), a freely accessible web-based data repository, has been developed to assist in a broad array of metabolite research and to facilitate metabolite identification through mass analysis. METLINincludes an annotated list of known metabolite structural information that is easily cross-correlated with its catalogue of high-resolution Fourier transform mass spectrometry (FTMS) spectra, tandem mass spectrometry (MS/MS) spectra, and LC/MS data.